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dc.contributor.author Pankajbhai, Rathod Kunal
dc.contributor.author Tyagi, Sarthak
dc.date.accessioned 2024-05-27T05:47:11Z
dc.date.available 2024-05-27T05:47:11Z
dc.date.issued 2023-11-29
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/1617
dc.description.abstract Chemsules introduces a revolutionary approach to carcinogenicity assessment, anchored by the precision-driven Metabokiller machine learning model. Catering to a diverse user base, including researchers, scientists, industry professionals, students, and enthusiasts, the platform offers a seamless web interface for compound analysis. Metabokiller's comprehensive evaluation covers electrophilicity, proliferation induction, oxidative stress, genomic instability, epigenome alterations, and anti-apoptotic response, providing a holistic understanding of compound carcinogenicity. The website features intuitive input methods, including SMILES string entry and graphical structure depiction. Ensuring data integrity and user confidentiality, the platform's scalability is showcased through an API for further development. This user-centric approach aims to democratize access to predictive insights, fostering advancements in compound carcinogenicity understanding. en_US
dc.language.iso en_US en_US
dc.publisher IIIT-Delhi en_US
dc.subject Carcinogenicity prediction en_US
dc.subject Metabokiller en_US
dc.subject machine learning en_US
dc.subject predictive methodologies en_US
dc.subject SMILES en_US
dc.subject compound analysis en_US
dc.subject user-centric interface en_US
dc.subject API integration en_US
dc.title Development of chemsules en_US
dc.type Other en_US


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